1. Technical Field
Embodiments of the subject matter disclosed herein generally relate to methods and systems and, more particularly, to mechanisms and techniques for more efficiently providing an accurate image of a subsurface structure.
2. Discussion of the Background
During the past years, the interest in developing new oil and gas production fields has dramatically increased. However, the availability of land-based production fields is limited. Thus, the industry has now extended drilling to offshore locations, which appear to hold a vast amount of fossil fuel. Offshore drilling is an expensive process. Thus, those undertaking the offshore drilling need to know where to drill in order to avoid a dry well.
Marine seismic data acquisition and processing generate a profile (image) of the geophysical structure under the seafloor. While this profile does not provide an accurate location for the oil and gas, it suggests, to those trained in the field, the presence or absence of oil and/or gas. Thus, providing a high resolution image of the structures under the seafloor is an ongoing process.
During a seismic gathering process, as shown in FIG. 1, a vessel 10 drags an array of acoustic detectors 12 that are provided on cable 14; the detectors 12 and the cable 14 are known as a streamer 16; the vessel 10 may drag plural streamers. The streamers may be disposed horizontally, i.e., lying at a constant depth Z1 relative to a surface 18 of the ocean. The vessel 10 also drags a sound source assembly 20 that is configured to generate an acoustic wave 22a. The acoustic wave 22a propagates downwards toward the seafloor 24 and penetrates the seafloor until eventually a reflecting structure R (reflector), on layer interface 26, reflects the acoustic wave. The reflected acoustic wave 22b propagates upwardly until it is detected by detector 12. Another reflected acoustic wave 22c propagates upwardly to the surface 18 and is then reflected back, 22d, to be detected by detector 12. The recorded data related to the detected waves is then processed for producing an accurate image of the subsurface. The processing includes various phases, e.g., velocity model determination, prestack, migration, poststack, etc., which are known in the art and thus, their description is omitted herein.
Progress in prestack depth imaging has been considerable in the past. The theoretical progress has provided better methods for extrapolating wavefields measured at the earth's surface into the subsurface, and the practical progress has linked the migrations more closely with velocity model building and interpretation. Migration is the process of propagating, for example, a wavefield measured at a receiver location to a reflector located in the subsurface. The migration may also be applied to wavefields generated by a source.
In complex subsurface areas, imaging difficulties are due to two components: prestack depth velocity model building and migration algorithms. Velocity model building estimates a velocity model (e.g., how the sound wave propagates through the various layers of the earth) for the simulation of seismic wave propagation that takes place during migration. This model forms the long wavelength (macro) part of the earth model, and the migration provides the short wavelength (reflectivity) part. Seismic ray-based tomography is a widely used tool for model building, but the nonlinearity and uncertainty of the ray-based tomography algorithms exposes tomography as a weak link in the imaging process.
Another weak link in the imaging process is the poor seismic illumination of regions beneath the complex overburden (e.g., salts, overthrusts structures, etc.), which makes adequate imaging difficult or even impossible. The overburden Poor illumination is often caused by inadequate seismic acquisition, for example, by conventional 3D narrow azimuth streamer acquisition when 3D wide azimuth acquisition is needed.
Until recently, Kirchhoff migration has been the workhorse method for prestack depth migration. This method has proven successful over numerous examples when the velocity variations are minor. This method has also formed the basis for the “true-amplitude” migration. This algorithm migrates the input seismic data one trace at a time or one local group of traces at a time; these processes imply that the cost of Kirchhoff migration is proportional to the number of input traces. However, when the number of input traces is relatively small within the migration aperture (as is usually the case with marine narrow azimuth surveys), Kirchhoff migration yields an efficient algorithm. On the contrary, when the number of input traces is large within the migration aperture (as is usually the case with marine wide azimuth surveys), efficiency might be lost as the computational task becomes demanding.
Also, using raytracing to approximate the Green's function of wave propagation may compromise the accuracy of Kirchhoff migration, especially when the wavefield is complicated. A traditional approximation, e.g., choosing a single ray arrival of the complicated wavefield at each image location, determines a noisy image in areas where there are many ray arrivals. Multi-arrival Kirchhoff migration algorithms overcome this problem, but they tend to be complicated and relatively inefficient in 3 dimension (3D).
According to other approaches, beam prestack depth migration methods approximate the Green's function with an expression that allows multiple arrivals to be imaged without excessive algorithmic complication, and it can be applied in a true-amplitude sense. As for Kirchhoff migration, however, the Green's function approximation used by beam migration relies on ray tracing and can become inaccurate if the migration velocity model contains extremely strong variations (e.g., salt bodies) and requires excessive smoothing. Still, the beam migration's ability to image complex structures and to control certain types of migration noise can usually ensure significantly better images in complex areas than single arrival Kirchhoff migration algorithms.
While Kirchhoff and beam migration methods use rays to approximate the Green's functions for wave propagation, so-called wave-equation migration algorithms use full waveform Green's functions that are numerically generated, for example by finite differences. The most computationally efficient algorithms for doing this are collectively called one-way wave equation migration (OWEM). These algorithms decompose seismic wavefields inside the earth into up-going waves and down-going waves under the assumption of no interaction between these two wavefields; that is, no turning wave and vertical reflection generation during the synthesis of wave propagation. Over a very large and growing body of examples, OWEM has solved the problems of multi-arrivals better than single arrival Kirchhoff migration. For wide azimuth seismic surveys, where the number of input traces is large compared with the migration aperture, OWEM tends to gain efficiency relative to Kirchhoff migration. For such surveys, efficient implementation of OWEM algorithms can be built either for common shot migration or for plane wave migration.
However, there are some major limitations of OWEM algorithms. First, turning waves are missing in the wave propagation synthesis, which results in the high dip events around 90° being poorly imaged; second, the wave propagation synthesis only ensures the accuracy of the phase of the wavefield, while amplitudes of the wavefield are much less reliable and need further correction.
Use of the two-way wave equation in depth migration began some time ago in an algorithm called reverse-time migration (RTM). However, this approach was limited due to its need for computer power. With increases in computer power, RTM has developed rapidly over the last few years, and theoretical advantages such as dip-unlimited accurate wave propagation and improved amplitudes have provided imaging benefits in practice. For example, in complex subsalt and salt flank areas, the numerical Green's functions from finite difference to the two-way wave equation have better amplitude behavior, so it is easier to incorporate amplitude corrections into RTM than into OWEM. In addition to its ability to handle complex velocities distributions, many current RTM algorithms can handle anisotropic media such as vertical transverse isotropy (VTI) and tilted transverse isotropy (TTI). On real data imaging examples, TTI RTM has given the best images in a complex Gulf of Mexico wide azimuth survey, though the velocity models for TTI migration were simplified as structurally conformable transversely isotropy (STI), which requires the anisotropic symmetric axis consistent with the reflectors' normal vectors.
With the improved accuracy of RTM comes increased sensitivity to the accuracy of the velocity model. This sensitivity causes notable improvement in RTM images when the velocity model is accurate, but it also causes notable degradation of RTM images when the velocity model is not accurate. For this reason, migration velocity analysis is more important for RTM than it is for other depth migration methods.
The link between migration and velocity model building is a set of common image gathers (CIGs) produced by the migration algorithms. A CIG is a set of images, all at the same image location (usually at the location of the reflector in the subsurface), with each image formed from different subsets of input data. For example, a single common offset/common azimuth data volume, which is a subset of the full acquired prestack seismic data set, can be used to 3D image the earth. The collection of images from all the sub-datasets with different offset and azimuth forms the CIGs. The CIGs include plural traces. The CIGs can have all traces with different offsets (with all the azimuthal information summed together), or the CIGs can have all traces with different offsets and azimuths.
The CIGs are commonly used for depth domain amplitude variation with offset (AVO) analysis, and migration-based velocity analysis. With a correct velocity model, all the images at the same image location should focus at the same depth, causing reflection events on the CIGs to appear flat. The flatness of seismic events on CIGs is one of the criteria for validating the velocity model by focusing analysis. When events on the CIGs are not flat, geophysicists improve their migration velocity models by analyzing the curvature of the events, using the analysis to guide a velocity update.
For Kirchhoff migration, there is no significant additional cost to compute common offset CIGs (COCIGs). On the other hand, migrating common-offset volumes by OWEM or RTM is expensive, so COCIGs are not generally available for those migration methods.
The quality limitations of COCIGs are caused, in part, by the underlying limitations of ray-based migration. More fundamentally, COCIGs suffer from migration artifacts due to multiple paths of wave propagation, whether or not the migration methods are capable of handling multiple paths of wavefield accurately, potentially causing difficulties for velocity analysis and amplitude versus reflection angle (AVA) analysis. In fact, CIGs whose traces are indexed by any attribute on the recording surface, such as source/receiver offset or surface incidence angle of the source energy, are susceptible to such artifacts. In this regard, it was showed that a necessary condition for artifact-free CIGs is to be parameterized in a subsurface angle domain, such as in a reflection angle or opening angle. This was illustrated in 2D using multi-arrival Kirchhoff migration on the Marmousi synthetic dataset and subsequent work has extended this showing to anisotropic media, or 3D using CIGs in reflection angle/azimuth angle, and to 3D analysis in multiple angle domain (reflection angle, dip angle, azimuth angle etc.).
Compared with multi-arrival Kirchhoff and beam migrations, OWEM and RTM appear to have limited capabilities for CIGs indexed in the surface offset domain. In the subsurface angle domain, an approach was proposed that outputs local subsurface offset CIGs from OWEM and then convert them to subsurface (reflection) angle domain CIGs (ADCIGs). Converting local subsurface offset CIGs into ADCIGs has a simple form in the 2D isotropic case. This approach requires the migration imaging condition to be applied at a range of subsurface offsets, forming subsurface offset CIGs; next, a 2D Fourier transform is applied to the local offset CIG; then the transform wavenumber is mapped to the reflection angle. The procedure is performed gather by gather locally, and it is a reasonably efficient algorithm.
However, the gather conversion formula is complex in 3D as it requires producing the local subsurface offset CIGs indexed by offset X and offset Y, and a 5D Fourier transform to the local subsurface offset CIGs to the wavenumber domain, followed by a high dimensional mapping. For implementation, even producing a local subsurface offset vector (X, Y) CIGs from OWEM is computationally intensive. An alternative approach is to produce time delay CIGs, then to convert them to ADCIGs. The time delay CIG has only one additional axis on the images (delay time). An output of time delay CIG is 4D (x, y, z, delay time). However, for wide azimuth seismic data, the expected 3D ADCIGs are themselves 5D (x, y, z, and incident/reflection angle, azimuth angle), so the time shift imaging condition does not provide sufficient information for a full conversion into 3D ADCIGs when applied to wide azimuth seismic data. As a result, the final angle gathers generally lack azimuthal information. Furthermore, the conversion from one data domain to another suffers from sampling issues, possibly degrading the resolution of the final CIGs.
The above approaches to obtain ADCIGs for OWEM and RTM are indirect, proceeding through an intermediate (subsurface offset or image time lag) domain. It is also possible to compute ADCIG's by directly decomposing the wavefields in the subsurface into their local directional components. So far, this work has been performed on 2D or 3D isotropic migration algorithms, and produces ADCIGs only in the reflection angle (no azimuth). Further, this approach has been applied only to one-way wavefield propagators, making it difficult to retain reliable amplitude information. Although there are other differences between the propagators for OWEM and RTM, there is no essential strategic difference in the algorithms for CIG output.
Accordingly, it would be desirable to provide systems and methods that avoid the afore-described problems and drawbacks.